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  • 1
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Programming languages (Electronic computers) ; Data mining ; Electronic books ; Electronic books ; local
    Abstract: Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination. You'll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Müller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book. With this book, you'll learn: Fundamental concepts and applications of machine learning Advantages and shortcomings of widely used machine learning algorithms How to represent data processed by machine learning, including which data aspects to focus on Advanced methods for model evaluation and parameter tuning The concept of pipelines for chaining models and encapsulating your workflow Methods for working with text data, including text-specific processing techniques Suggestions for improving your machine learning and data science skills
    Note: Includes index. - Description based on online resource; title from title page (viewed October 6, 2016)
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  • 2
    Language: German
    Pages: 1 online resource (1 volume) , illustrations
    Edition: 1. Auflage 2017.
    Keywords: Machine learning ; Python (Computer program language) ; Artificial intelligence ; Electronic books ; Electronic books ; local
    Abstract: Machine Learning ist zu einem wichtigen Bestandteil vieler kommerzieller Anwendungen und Forschungsprojekte geworden, von der medizinischen Diagnostik bis hin zur Suche nach Freunden in sozialen Netzwerken. Um Machine Learning-Anwendungen selbst zu entwickeln, braucht es keine großen Teams: Wenn Sie Python-Grundkenntnisse mitbringen, kann Ihnen dieses Praxisbuch zeigen, wie Sie Ihre eigenen Machine Learning-Lösungen entwickeln.Mit Python und der scikit-learn-Bibliothek erarbeiten Sie sich alle Schritte, die für eine erfolgreiche Machine Learning-Anwendung notwendig sind. Die Autoren Andreas Müller und Sarah Guido konzentrieren sich bei der Verwendung von Machine Learning-Algorithmen auf die Praxis und weniger auf die Mathematik dahinter. Wenn Sie zusätzlich mit den Bibliotheken NumPy und matplotlib vertraut sind, hilft Ihnen dies, noch mehr aus diesem Buch herauszuholen.
    Note: Includes index. - Description based on online resource; title from title page (viewed November 1, 2017)
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  • 3
    ISBN: 9788383227528 , 8383227523
    Language: Polish
    Pages: 1 online resource (320 pages) , illustrations
    Edition: [First edition].
    Uniform Title: Introduction to machine learning with Python
    DDC: 005.13/3
    Keywords: Machine learning ; Python (Computer program language) ; Data mining
    Abstract: Uczenie maszynowe kojarzy się z dużymi firmami i rozbudowanymi zespołami. Prawda jest taka, że obecnie można samodzielnie budować zaawansowane rozwiązania uczenia maszynowego i korzystać do woli z olbrzymich zasobów dostępnych danych. Trzeba tylko mieć pomysł i... trochę podstawowej wiedzy. Tymczasem większość opracowań na temat uczenia maszynowego i sztucznej inteligencji wymaga biegłości w zaawansowanej matematyce. Utrudnia to naukę tego zagadnienia, mimo że uczenie maszynowe jest coraz powszechniej stosowane w projektach badawczych i komercyjnych. Ta praktyczna książka ułatwi Ci rozpoczęcie wdrażania rozwiązań rzeczywistych problemów związanych z uczeniem maszynowym. Zawiera przystępne wprowadzenie do uczenia maszynowego i sztucznej inteligencji, a także sposoby wykorzystania Pythona i biblioteki scikit-learn, uwzględniające potrzeby badaczy i analityków danych oraz inżynierów pracujących nad aplikacjami komercyjnymi. Zagadnienia matematyczne ograniczono tu do niezbędnego minimum, zamiast tego skoncentrowano się na praktycznych aspektach algorytmów uczenia maszynowego. Dokładnie opisano, jak konkretnie można skorzystać z szerokiej gamy modeli zaimplementowanych w dostępnych bibliotekach.
    Note: Includes index
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  • 4
    ISBN: 9784873117980
    Language: English , Japanese
    Pages: 1 online resource (392 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Pythonの機械学習用ライブラリの定番、scikit-learnのリリースマネージャを務めるなど開発に深く関わる著者が、scikit-learnを使った機械学習の方法を、ステップバイステップで解説します。ニューラルネットを学ぶ前に習得しておきたい機械学習の基礎をおさえるとともに、優れた機械学習システムを実装し精度の高い予測モデルを構築する上で重要となる「特徴量エンジニアリング」と「モデルの評価と改善」について多くのページを割くなど、従来の機械学習の解説書にはない特長を備えています。
    Note: Online resource; Title from title page (viewed May 24, 2017) , Mode of access: World Wide Web.
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  • 5
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : Editions First | Boston, MA : Safari
    Language: English , French
    Pages: 1 online resource (364 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Entrez de plain-pied dans le monde fascinant la data science Vous aussi participez à la révolution qui ramène l'intelligence artificielle au coeur de notre société, grace aux data scientists. La data science consiste à traduire des problèmes de toute autre nature, en problèmes de modélisation quantitative, résolus par des algorithmes de traitement. Ce livre se présente comme une référence pour tous les développeurs, statisticiens ou chefs de projets ayant à résoudre des problèmes liés à la data science.
    Note: Online resource; Title from title page (viewed February 25, 2018) , Mode of access: World Wide Web.
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  • 6
    Online Resource
    Online Resource
    [Place of publication not identified] : O'Reilly Media
    ISBN: 9781491919217
    Language: English
    Pages: 1 online resource (1 streaming video file (37 min., 9 sec.)) , digital, sound, color.
    Keywords: Python (Computer program language) ; Application software ; Development ; Electronic videos ; local
    Abstract: "Python is quickly becoming the go-to language for data analysis, but it can be difficult to figure out which tools to use. In this webcast you'll get a bird's eye overview of some of the best tools for data analysis and how you can apply them to your workflow. She'll introduce you to how you can use Pandas, Scikit-Learn, NLTK, MRJob, and matplotlib for data analysis."--Resource description page.
    Note: Title from resource description page (viewed February 12, 2015)
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  • 7
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : Posts & Telecom Press
    ISBN: 9787115475619 , 711547561X
    Language: Undetermined
    Pages: 1 online resource
    Note: Title from content provider
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  • 8
    Title: 精通機器學習 : : 使用 Python = Introduction to machine learning with Python /
    ISBN: 9789864763665 , 9864763660
    Language: Chinese
    Pages: 1 online resource (384 pages) , illustrations
    Edition: [First edition].
    Uniform Title: Introduction to machine learning with Python
    DDC: 005.13/3
    Keywords: Machine learning ; Python (Computer program language) ; Data mining ; Data Mining ; Apprentissage automatique ; Python (Langage de programmation) ; Exploration de données (Informatique) ; Data mining ; Machine learning ; Python (Computer program language) ; Electronic books
    Abstract: Detailed summary in vernacular field.
    Note: Includes index
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